Informing a user of a large scale network dynamically of other network users includes determining dynamically an online context of the user. Other users presently within the online context of the user are identified and trait information is stored that is related essentially only to the user or to the other users in a users store associated with the online context. The user is informed dynamically of the other users based on the stored trait information, such as, for example, an age or other demographic identifier, or information indicative of an expertise, interest, preference, user type and/or other quality of the user or of the other individual.
Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method comprising: executing computer instructions upon one or more computer processors to perform the following: determining a first online context of a user, the first online context of the user being based upon a first online presence of the user; storing, in a database, trait information for the user, the trait information for the user being different from the first online context of the user; determining an online context of other users, the online context of the other users being based upon an online presence of the other users; comparing the first online context of the user to the online context of the other users; storing, in the database, trait information for the other users that have entered the first online context of the user, the trait information for the other users being different from the online context of the other users; comparing the stored trait information for the user to the stored trait information for the other users to identify a first group of the other users that share the first online context of the user and at least one trait with the user; enabling automatic presentation of a user interface to inform the user of at least one member of the identified first group of the other users that share the first online context of the user and at least one trait with the user; and dynamically updating the user interface, in response to the user switching to a second online context, to inform the user of at least one member of a second group of the other users that share the second online context of the user and at least one trait with the user.
The system dynamically identifies other users to an online user. It determines a user's current online context (e.g., a specific webpage or forum). It stores trait information about the user (e.g., age, interests) in a database, separate from the context. It also determines the online contexts of other users and stores their trait information if they're in the same online context as the first user. The system then compares the user's traits to the other users' traits to find users who share the context and at least one trait. Finally, it automatically updates a user interface to show the user a list of these matching users, and dynamically updates the UI as the user moves to new online contexts, showing new matching users.
2. The method of claim 1 , further comprising enabling the user to view a profile of the at least one member of the identified first group of the other users.
The system described for dynamically identifying other users to an online user allows the user to click on a listed user and view a profile page for that user. This builds upon the base functionality of determining a user's current online context; storing trait information about the user separate from their context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
3. The method of claim 1 , further comprising informing the user of the number of other users in the identified first group.
The system described for dynamically identifying other users to an online user also informs the user how many other users are in the identified group that shares their online context and at least one trait. For example, the UI might display "3 other users are in this forum and share your interest in Python." This builds upon the base functionality of determining a user's current online context; storing trait information about the user separate from their context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
4. The method of claim 1 , wherein determining the first online context of the user comprises determining a category identifier that defines the first online context.
In the system for dynamically identifying other users to an online user, determining a user's online context involves assigning a category identifier. For example, the URL `example.com/sports/baseball` might be assigned the category ID "baseball". The system would then use this ID for comparisons. This is used in conjunction with storing trait information about the user separate from their context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
5. The method of claim 1 , further comprising: determining whether the at least one member of the identified first group of the other users has opted out of participation; and informing the user of the at least one member of the identified first group of the other users if the at least one member has not opted out of participation.
The system described for dynamically identifying other users to an online user first checks if potential matches have opted out of being shown to other users. It only informs the user of other users who *haven't* opted out. This builds upon the base functionality of determining a user's current online context; storing trait information about the user separate from their context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
6. The method of claim 1 , further comprising enabling the user to interact with the at least one member of the identified first group by way of the user interface.
The system described for dynamically identifying other users to an online user enables direct interaction between the user and the identified other users via the user interface. This could include features like direct messaging or shared activity feeds. This builds upon the base functionality of determining a user's current online context; storing trait information about the user separate from their context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
7. The method of claim 1 , further comprising rating the identified first group of the other users based on predetermined expertise categories.
The system described for dynamically identifying other users to an online user rates the identified other users based on pre-defined expertise categories. These ratings are then used to prioritize or filter the list of users shown to the user. This builds upon the base functionality of determining a user's current online context; storing trait information about the user separate from their context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
8. The method of claim 1 , further comprising: selecting users from the identified first group of the other users, wherein the selected users have an expertise requested by the user; rating the level of expertise of the selected users; and presenting a list of selected users sorted by their rating to the user.
The system described for dynamically identifying other users to an online user allows a user to request users with specific expertise. It then selects users from the matching group who have that expertise, rates their level of expertise, and presents a sorted list to the user. This builds upon the base functionality of determining a user's current online context; storing trait information about the user separate from their context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
9. The method of claim 8 , further comprising presenting the user with a list of online identifiers of the selected users, wherein the online identifiers of the selected users with ratings higher than a predetermined threshold are highlighted.
The system described for dynamically identifying other users to an online user shows a list of online identifiers (e.g., usernames) of users with expertise requested by the user, sorted by their expertise rating. The system highlights the identifiers of those whose rating is above a certain threshold to visually prioritize them. This extends the features of selecting users from the identified group who have an expertise requested by the user; rating the level of expertise of the selected users; and presenting a list of selected users sorted by their rating to the user; building on the initial function of identifying other users who share an online context and at least one trait.
10. The method of claim 1 , wherein the first online context of the user comprises at least one of an Internet domain, a newsgroup, a message board, a URL, or a portion of a web page currently accessed by the user.
The system described for dynamically identifying other users to an online user determines a user's online context by considering things like the Internet domain they're visiting, a newsgroup they're participating in, a message board, a URL they're accessing, or even a specific part of a webpage they're viewing. The trait information is stored about the user, separate from their context; determines the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
11. The method of claim 1 , wherein the trait information for the user comprises at least one of an age, a demographic identifier, an expertise rating, an interest, or a participation status.
The system described for dynamically identifying other users to an online user stores trait information about users, including things like their age, demographic, expertise rating, interests, or participation status. This information is stored in a database and used to match users who share a context and at least one trait. This enables the system determining a user's current online context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
12. The method of claim 1 , further comprising dynamically updating the user interface to reflect changes to the group of the other users that share the first online context of the user and at least one trait with the user.
The system described for dynamically identifying other users to an online user keeps the user interface updated in real-time to reflect changes in the group of other users that share the user's current online context and at least one trait. If a user leaves the context, or a new user joins, the interface dynamically reflects the changes. This builds upon the base functionality of determining a user's current online context; storing trait information about the user separate from their context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
13. A system comprising at least one processor connected to a storage device, wherein the at least one processor is configured to: determine a first online context of a user, the first online context of the user being based upon a first online presence of the user; store, in a database, trait information for the user, the trait information for the user being different from the first online context of the user; determine an online context of other users, the online context of the other users being based upon an online presence of the other users; compare the first online context of the user to the online context of the other users; store, in the database, trait information for the other users that have entered the first online context of the user, the trait information for the other users being different from the online context of the other users; compare the stored trait information for the user to the stored trait information for the other users to identify a first group of the other users that share the first online context of the user and at least one trait with the user; enable automatic presentation of a user interface to inform the user of at least one member of the identified first group of the other users that share the first online context of the user and at least one trait with the user; and dynamically update the user interface, in response to the user switching to a second online context, to inform the user of al least one member of second group of the other users that share the second online context of the user and at least one trait with the user.
A computer system dynamically identifies other users to an online user. The system has a processor and storage. The processor determines a user's current online context (e.g., a specific webpage or forum). It stores trait information about the user (e.g., age, interests) in a database, separate from the context. It also determines the online contexts of other users and stores their trait information if they're in the same online context as the first user. The processor then compares the user's traits to the other users' traits to find users who share the context and at least one trait. Finally, it automatically updates a user interface to show the user a list of these matching users, and dynamically updates the UI as the user moves to new online contexts, showing new matching users.
14. The system of claim 13 , wherein the processor is further configured to: determine whether the at least one member of the identified first group of the other users has opted out of participation; and inform the user of the at least one member of the identified first group of the other users if the at least one member has not opted out of participation.
The system described, having a processor and storage for dynamically identifying other users to an online user, first checks if potential matches have opted out of being shown to other users. The processor only informs the user of other users who *haven't* opted out. This builds upon the base functionality of determining a user's current online context; storing trait information about the user separate from their context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
15. The system of claim 13 , wherein the processor is further configured to enable the user to interact with the at least one member of the identified first group of other users by way of the user interface.
The system described, having a processor and storage for dynamically identifying other users to an online user, enables direct interaction between the user and the identified other users via the user interface. This could include features like direct messaging or shared activity feeds. This builds upon the base functionality of determining a user's current online context; storing trait information about the user separate from their context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
16. The system of claim 13 , wherein the processor is further configured to: select users from the identified first group of the other users, wherein the selected users have an expertise requested by the user; rate the level of expertise of the selected users; and present a list of selected users sorted by their rating to the user.
The system described, having a processor and storage for dynamically identifying other users to an online user, allows a user to request users with specific expertise. The processor then selects users from the matching group who have that expertise, rates their level of expertise, and presents a sorted list to the user. This builds upon the base functionality of determining a user's current online context; storing trait information about the user separate from their context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
17. The system of claim 13 , wherein the first online context of the user comprises at least one of an Internet domain, a newsgroup, a message board, a URL, or a portion of a web page currently accessed by the user.
In the system described, having a processor and storage for dynamically identifying other users to an online user, the processor determines a user's online context by considering things like the Internet domain they're visiting, a newsgroup they're participating in, a message board, a URL they're accessing, or even a specific part of a webpage they're viewing. The system then stores trait information about the user, separate from their context; determines the online contexts of other users and storing their trait information if they're in the same online context as the first user; compares traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
18. The system of claim 13 , wherein the trait information for the user comprises at least one of an age, a demographic identifier, an expertise rating, an interest, or a participation status.
In the system described, having a processor and storage for dynamically identifying other users to an online user, the system stores trait information about users, including things like their age, demographic, expertise rating, interests, or participation status. This information is stored in a database and used to match users who share a context and at least one trait. This enables the system determining a user's current online context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
19. The system of claim 13 , wherein the processor is further configured to dynamically update the user interface to reflect changes to the group of the other users that share the first online context of the user and at least one trait with the user.
The system described, having a processor and storage for dynamically identifying other users to an online user, keeps the user interface updated in real-time to reflect changes in the group of other users that share the user's current online context and at least one trait. If a user leaves the context, or a new user joins, the processor dynamically reflects the changes in the UI. This builds upon the base functionality of determining a user's current online context; storing trait information about the user separate from their context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
20. A non-transitory computer readable medium storing instructions for causing one or more processors to perform a method comprising: determining a first online context of a user, the first online context of the user being based upon a first online presence of the user; storing, in a database, trait information for the user, the trait information for the user being different from the first online context of the user; determining an online context of other user, the online context of the other users being based upon an online presence of the other users; comparing, with a processor, the first online context of the user to the online context of the other users; storing, in the database, trait information for the other users that have entered the first online context of the user, the trait information for the other users being different from the online context of the other users; comparing, with a processor, the stored trait information for the user to the stored trait information for the other users to identify a first group of the other users that share the first online context of the user and at least one trait with the user; enabling automatic presentation of a user interface to inform the user of at least one member of the identified first group of the other users that share the first online context of the user and at least one trait with the user; and dynamically updating the user interface, in response to the user switching to a second online context, to inform the user of at least one member of a second group of the other users that share the second online context of the user and at least one trait with the user.
Computer-readable instructions, when executed, cause a system to dynamically identify other users to an online user. The system determines a user's current online context (e.g., a specific webpage or forum). It stores trait information about the user (e.g., age, interests) in a database, separate from the context. It also determines the online contexts of other users and stores their trait information if they're in the same online context as the first user. The system then compares the user's traits to the other users' traits to find users who share the context and at least one trait. Finally, it automatically updates a user interface to show the user a list of these matching users, and dynamically updates the UI as the user moves to new online contexts, showing new matching users.
21. The non-transitory computer readable medium of claim 20 , the method further comprising enabling the user to view a profile of the at least one member of the identified first group of the other users.
The computer-readable instructions described, for dynamically identifying other users to an online user, when executed, further allow the user to click on a listed user and view a profile page for that user. This builds upon the base functionality of determining a user's current online context; storing trait information about the user separate from their context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
22. The non-transitory computer readable medium of claim 20 , the method further comprising informing the user of the number of other users in the identified first group.
The computer-readable instructions described, for dynamically identifying other users to an online user, when executed, also inform the user how many other users are in the identified group that shares their online context and at least one trait. For example, the UI might display "3 other users are in this forum and share your interest in Python." This builds upon the base functionality of determining a user's current online context; storing trait information about the user separate from their context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
23. The non-transitory computer readable medium of claim 20 , wherein determining the first online context of the user comprises determining a category identifier that defines the first online context.
In the computer-readable instructions described, for dynamically identifying other users to an online user, determining a user's online context involves assigning a category identifier. For example, the URL `example.com/sports/baseball` might be assigned the category ID "baseball". The system would then use this ID for comparisons. This is used in conjunction with storing trait information about the user separate from their context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
24. The non-transitory computer readable medium of claim 20 , the method further comprising: determining whether the at least one member of the identified first group of the other users has opted out of participation; and informing the user of the at least one member of the identified first group of the other users if the at least one member has not opted out of participation.
The computer-readable instructions described, for dynamically identifying other users to an online user, when executed, first checks if potential matches have opted out of being shown to other users. It only informs the user of other users who *haven't* opted out. This builds upon the base functionality of determining a user's current online context; storing trait information about the user separate from their context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
25. The non-transitory computer readable medium of claim 20 , further comprising enabling the user to interact with the at least one member of the identified first group of other users by way of the user interface.
The computer-readable instructions described, for dynamically identifying other users to an online user, when executed, enable direct interaction between the user and the identified other users via the user interface. This could include features like direct messaging or shared activity feeds. This builds upon the base functionality of determining a user's current online context; storing trait information about the user separate from their context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
26. The non-transitory computer readable medium of claim 20 , the method further comprising: selecting users from the identified first group of the other users, wherein the selected users have an expertise requested by the user; rating the level of expertise of the selected users; and presenting a list of selected users sorted by their rating to the user.
The computer-readable instructions described, for dynamically identifying other users to an online user, when executed, allow a user to request users with specific expertise. It then selects users from the matching group who have that expertise, rates their level of expertise, and presents a sorted list to the user. This builds upon the base functionality of determining a user's current online context; storing trait information about the user separate from their context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
27. The non-transitory computer readable medium of claim 20 , wherein the first online context of the user comprises at least one of an Internet domain, a newsgroup, a message board, a URL, or a portion of a web page currently accessed by the user.
The computer-readable instructions described, for dynamically identifying other users to an online user, when executed, determines a user's online context by considering things like the Internet domain they're visiting, a newsgroup they're participating in, a message board, a URL they're accessing, or even a specific part of a webpage they're viewing. The system then stores trait information about the user, separate from their context; determines the online contexts of other users and storing their trait information if they're in the same online context as the first user; compares traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
28. The non-transitory computer readable medium of claim 20 , wherein the trait information for the user comprises at least one of an age, a demographic identifier, an expertise rating, an interest, or a participation status.
The computer-readable instructions described, for dynamically identifying other users to an online user, when executed, store trait information about users, including things like their age, demographic, expertise rating, interests, or participation status. This information is stored in a database and used to match users who share a context and at least one trait. This enables the system determining a user's current online context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
29. The non-transitory computer readable medium of claim 20 , the method further comprising dynamically updating the user interface to reflect changes to the group of the other users that share the first online context of the user and at least one trait with the user.
The computer-readable instructions described, for dynamically identifying other users to an online user, when executed, keeps the user interface updated in real-time to reflect changes in the group of other users that share the user's current online context and at least one trait. If a user leaves the context, or a new user joins, the interface dynamically reflects the changes. This builds upon the base functionality of determining a user's current online context; storing trait information about the user separate from their context; determining the online contexts of other users and storing their trait information if they're in the same online context as the first user; comparing traits to find users who share context and traits; and automatically updating a user interface to show the user a list of matching users that dynamically updates as the user moves to new online contexts.
Cooperative Patent Classification codes for this invention. Click any code to explore related patents in that topic.
February 8, 2011
May 9, 2017
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